roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: {{ template "name" . }}
subjects:
- kind: ServiceAccount
  name: {{ template "name" . }}
  namespace: {{ .Release.Namespace }}
---
{{- if .Values.cni.repair.enabled }}
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: {{ template "name" . }}-repair-rolebinding
  labels:

#include "tensorflow/c/experimental/ops/gen/model/arg_spec.h"
#include "tensorflow/c/experimental/ops/gen/model/attr_spec.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {
namespace cpp {

string OpArgumentView::Declaration() const {
  return absl::Substitute("$0 $1", type_name_, variable_name_);
}

string OpArgumentView::Initializer() const {

# Pod must be before namespace, so it initially fails. Second
# apply of pod should succeed, since namespace finally exists.
apiVersion: v1
kind: Pod
metadata:
  name: test-pod
  namespace: multi-resource-ns
  labels:
    name: test-pod-label
spec:
  containers:
  - name: kubernetes-pause
    image: registry.k8s.io/pause:3.10
---
apiVersion: v1
kind: Namespace
metadata:

#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"
#include "tsl/platform/errors.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {
namespace {

constexpr char kEntryFuncName[] = "main";

absl::Status SetupArguments(mlir::ModuleOp module,
                            std::vector<TensorShape>& arg_shapes,

#include "tensorflow/c/experimental/ops/gen/model/arg_type.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {
namespace cpp {

ArgTypeView::ArgTypeView(ArgType arg_type) : arg_type_(arg_type) {}

string ArgTypeView::TypeName() const {
  if (arg_type_.is_read_only()) {
    if (arg_type_.is_list()) {

		"Capacity in bytes of the volume",
		[]string{"namespace", "persistentvolumeclaim"}, nil,
		metrics.ALPHA, "",
	)
	volumeStatsAvailableBytesDesc = metrics.NewDesc(
		metrics.BuildFQName("", kubeletmetrics.KubeletSubsystem, kubeletmetrics.VolumeStatsAvailableBytesKey),
		"Number of available bytes in the volume",
		[]string{"namespace", "persistentvolumeclaim"}, nil,
		metrics.ALPHA, "",
	)

	Address   string
	Node      string
	Namespace string
}

// Verify returns true if the passed workload matches the filter fields
func (wf *WorkloadFilter) Verify(workload *ZtunnelWorkload) bool {
	if wf.Address == "" && wf.Node == "" && wf.Namespace == "" {
		return true
	}

	if wf.Namespace != "" {
		if !strings.EqualFold(workload.Namespace, wf.Namespace) {
			return false
		}
	}

type PolicyFilter struct {
	Namespace string
}

// Verify returns true if the passed workload matches the filter fields
func (wf *PolicyFilter) Verify(pol *ZtunnelPolicy) bool {
	if wf.Namespace != "" {
		if !strings.EqualFold(pol.Namespace, wf.Namespace) {
			return false
		}
	}

	return true
}

#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/platform/resource_loader.h"
#include "tsl/lib/core/status_test_util.h"
#include "tsl/platform/status.h"

namespace tensorflow {
namespace tf2xla {
namespace v1 {
namespace {

using ::mlir::DialectRegistry;
using ::mlir::MLIRContext;
using ::mlir::ModuleOp;
using ::mlir::OwningOpRef;
using ::tensorflow::monitoring::testing::CellReader;

#include "tensorflow/core/lib/monitoring/cell_reader.h"
#include "tensorflow/core/platform/resource_loader.h"
#include "tsl/lib/core/status_test_util.h"

namespace tensorflow {
namespace tf2xla {
namespace v2 {
namespace {

constexpr char kExportStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/tf_dialect_to_executor_dialect_status";
constexpr char kExportSuccess[] = "success";